A database of cross-sectional images for testing the biometric traceability of oak (Quercus petraea (Matt.) Liebl. and Quercus robur L.) logs under realistic acquisition conditions

Key message The Biomtrace_extension database contains 8341 RGB images of the butt end of 695 French oak logs. This database was created with the aim of developing biometric traceability methods based on realistic photo acquisitions in the field for tracking logs from the forest to primary processing. No such database was previously available. Photos of the same logs were taken on two dates several months apart, up to more than 100 days apart for some sites. Images were acquired in three specific cases in order to test the sensitivity and limitations of recognition algorithms under conditions that may occur in practice: (1) traceability based on photos taken before and after log extraction; (2) sensitivity of traceability to the quality of photos (angle of the shot and distance to the log); (3) robustness of traceability to partial or complete trimming of the log end. The database also includes manual reference measurements performed on the images, as well as outputs from image preprocessing algorithms. Tables containing site and image characteristics are also provided. The Biomtrace_extension database is available at https://doi.org/10.57745/RKDTKY and metadata are provided at: https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/5f2842a0-15ec-48be-8f1c-e44334654cc5 .

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Publication Details

Journal
Annals of Forest Science
Published
2026-03-31
DOI
https://doi.org/10.1186/s13595-026-01330-0
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
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article

A database of cross-sectional images for testing the biometric traceability of oak (Quercus petraea (Matt.) Liebl. and Quercus robur L.) logs under realistic acquisition conditions

Fleur Longuetaud, Aymeric Albert, C. RICHTER, Isabelle Debled-Rennesson et al.
Annals of Forest Science
Remote Sensing and LiDAR Applications
article

A database of cross-sectional images for testing the biometric traceability of oak (Quercus petraea (Matt.) Liebl. and Quercus robur L.) logs under realistic acquisition conditions

Fleur Longuetaud, Aymeric Albert, C. RICHTER, Isabelle Debled-Rennesson, Alexandre Piboule, Bruno Vuidel, Daniel Rittié, Frédéric Bordat, Frédéric Mothe, Phuc Ngo, Philippe Jacquin, Dorian Martinetto
article en

Abstract

Key message The Biomtrace_extension database contains 8341 RGB images of the butt end of 695 French oak logs. This database was created with the aim of developing biometric traceability methods based on realistic photo acquisitions in the field for tracking logs from the forest to primary processing. No such database was previously available. Photos of the same logs were taken on two dates several months apart, up to more than 100 days apart for some sites. Images were acquired in three specific cases in order to test the sensitivity and limitations of recognition algorithms under conditions that may occur in practice: (1) traceability based on photos taken before and after log extraction; (2) sensitivity of traceability to the quality of photos (angle of the shot and distance to the log); (3) robustness of traceability to partial or complete trimming of the log end. The database also includes manual reference measurements performed on the images, as well as outputs from image preprocessing algorithms. Tables containing site and image characteristics are also provided. The Biomtrace_extension database is available at https://doi.org/10.57745/RKDTKY and metadata are provided at: https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/5f2842a0-15ec-48be-8f1c-e44334654cc5 .

Annals of Forest ScienceVol. 83(1)
Centre National de la Recherche Scientifique (FR), AgroParisTech (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Silva (FR), Office National des Forêts (FR), Laboratoire Lorrain de Recherche en Informatique et ses Applications (FR), Université de Lorraine (FR)
Life in Land
Openalex Percentile: Top 36%
Remote Sensing and LiDAR Applications
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